scholarly journals On the modified random walk algorithm for Monte-Carlo radiation transfer(Corrigendum)

2015 ◽  
Vol 576 ◽  
pp. C1
Author(s):  
T. P. Robitaille
Keyword(s):  
Monte Carlo ◽  
Random Walk ◽  
Radiation Transfer ◽  
Random Walk Algorithm ◽  
Walk Algorithm

Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm

2014 ◽  
Vol 38 (8) ◽  
pp. 753-763 ◽  
Author(s):  
D.P. Onoma ◽  
S. Ruan ◽  
S. Thureau ◽  
L. Nkhali ◽  
R. Modzelewski ◽  
...  
Keyword(s):  
Random Walk ◽  
Fdg Pet ◽  
Random Walk Algorithm ◽  
Locally Adaptive ◽  
Walk Algorithm

AN IMPROVED RANDOM WALK SEGMENTATION ON THE LUNG NODULES

2013 ◽  
Vol 06 (06) ◽  
pp. 1350043 ◽  
Author(s):  
LI GUO ◽  
YUNTING ZHANG ◽  
ZEWEI ZHANG ◽  
DONGYUE LI ◽  
YING LI
Keyword(s):  
Random Walk ◽  
Lung Nodule ◽  
Texture Feature ◽  
Ellipse Fitting ◽  
Lung Nodule Detection ◽  
Random Walk Algorithm ◽  
Fitting Algorithm ◽  
Nodule Detection ◽  
Walk Algorithm ◽  
Automatic Technique

In this paper, we proposed a semi-automatic technique with a marker indicating the target to locate and segment nodules. For the lung nodule detection, we develop a Gabor texture feature by FCM (Fuzzy C Means) segmentation. Given a marker indicating a rough location of the nodules, a decision process is followed by applying an ellipse fitting algorithm. From the ellipse mask, the foreground and background seeds for the random walk segmentation can be automatically obtained. Finally, the edge of the nodules is obtained by the random walk algorithm. The feasibility and effectiveness of the proposed method are evaluated with the various types of the nodules to identify the edges, so that it can be used to locate the nodule edge and its growth rate.

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